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Why We Built Sahkarmi: The Open-Source AI Coworker That Never Acts Without Your Approval

#agents #ai #showdev #opensource

By Dhrubojyoti Gangopadhyay (Founder, Sahkarmi)

Website: sahkarmi.site | GitHub: github.com/ganguydhrubo/sahakarmi | License: Apache-2.0

The AI Agent Dilemma: Autonomy vs. Control

Over the past two years, the promise of autonomous AI agents has captured the imagination of every software engineer and startup founder. We were told agents would write our code, debug production incidents, handle customer support, and deploy our cloud infrastructure while we sleep.

Yet in practice, most developers still hesitate to hand full control over to autonomous scripts. Why?

  1. Unpredictable Destructive Actions: An autonomous script with bash access can easily run rm -rf, drop a database table during a migration attempt, or overwrite critical configuration files.
  2. Cloud Lock-in & Privacy Leaks: Sending proprietary codebases, database schemas, and private API tokens to third-party hosted agent clouds poses major enterprise security and data privacy risks.
  3. The Black Box Problem: When an agent works in the background without real-time observability, catching mistakes requires tedious forensic post-mortems after damage is already done.

We asked ourselves: What if autonomous AI agents didn't replace human judgement, but instead operated like trusted colleagues with built-in human verification gates?

That is why we built Sahkarmi (सहकर्मी) — the Hindi word for coworker.

What is Sahkarmi?

Sahkarmi is an open-source desktop team workspace where autonomous AI coworkers run locally on your own machine.

Unlike traditional scripts or chat windows, Sahkarmi's agents are equipped with specialized tools — a sandboxed local terminal, filesystem access, an embedded Chromium browser, and persistent long-term memory — while strictly obeying a single foundational principle:

Zero Unapproved Impact: An agent can plan, inspect files, draft code, and browse documentation autonomously; but the moment it attempts a sensitive action — such as executing a shell command, writing a file, submitting a web form, or executing a transaction — it pauses and presents a clear, interactive Human-in-the-Loop Approval Card.

[ Sahkarmi Human Verification Card ]
--------------------------------------------------
Task: Deploy backend schema migration
Agent: Dev_Backend_Coworker
Proposed Command: python manage.py migrate --database=prod
Working Dir: /home/user/project

[ APPROVE ]     [ REJECT ]     [ REVISE ]
--------------------------------------------------
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You maintain complete oversight. You can approve with a single keystroke, reject with corrective feedback, or take over directly.

Under the Hood: The 3-Tier Architecture

1. The Supervised Desktop Interface (Electron + React)

  • Multi-Agent Tabs: Collaborate simultaneously with specialized coworkers (Code Reviewer, Growth Engineer, System Admin).
  • Embedded Chromium Engine: Watch your AI coworker navigate websites, test web applications, and take snapshots beside your conversation thread.
  • Code Diff & Terminal Stream: Real-time syntax-highlighted diffs and streaming terminal stdout/stderr.

2. Local Memory & Routine Engine

  • Persistent Knowledge Graph: Coworkers remember your project architecture, tech stack preferences, and past decisions across sessions.
  • Background Scheduled Routines: Define cron-like recurring jobs (check PR reviews every 3 hours, monitor error logs, reconcile ledgers) that trigger autonomously.

3. Sandboxed Tool Execution (Model Context Protocol / MCP)

  • Local Shell & File Operations: Run builds, tests, git commits, and linters directly on your machine.
  • Strict Security Boundaries: Passwords, OTPs, and card details are NEVER typed by the agent. If an authentication challenge arises, the agent hands over the browser or requests secure input from you.

Provider Agnostic: Bring Your Own Models

Sahkarmi never locks you into a proprietary LLM API. You can switch models per task:

  • Local Privacy: Connect to Ollama or vLLM to run Llama, DeepSeek, or Qwen fully offline, with zero cloud data transmission.
  • High-Reasoning Cloud: Plug in your own API keys for Google Gemini, Anthropic Claude, or OpenAI models.

Getting Started

Sahkarmi is free and open-source under the Apache-2.0 license.

Platform support, honestly stated: Sahkarmi ships a Windows 10/11 (x64) desktop build today. macOS and Linux are planned but are not released yet — installer scripts exist in the repository but are not used for releases.

Download the Windows installer

Grab the latest signed release directly:

  • sahkarmi.site — download button always points at the current release
  • Or from GitHub Releases, with a published SHA256SUMS-windows.txt so you can verify the download before running it.

Build from source 

git clone https://github.com/ganguydhrubo/sahakarmi.git
cd sahakarmi
bun install
bun run dev
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Package managers

WinGet and Scoop manifests are submitted and currently awaiting review by their respective communities. Once those land, installation will also be a one-liner. Until then, please use the direct download above.

Join the Community

We believe the future of software development belongs to collaborative human-AI teams, where humans provide intent and strategic oversight while autonomous coworkers handle the execution grind.

If you try it, I would genuinely like to hear where the approvals model gets in your way — that feedback is what shapes the roadmap.

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